Sentence examples for handle the variability from inspiring English sources

Assuming that average costs can approximate marginal costs, the marginal cost for precautionary measures is observable given appropriate company data, since firms are investing in their logistic systems to handle the variability in transportation times they are facing.

The availability of a set of reference key-poses makes it possible to obtain a reduced representation of each gesture sequence, able to handle the variability of gestures performed by different individuals.

However, when involving users in the comparison of search systems, methodological challenges still exist as researchers are pondering on how to handle the variability that human participants bring to the comparisons.

As the granularity increases, rounding is no longer sufficient for handling the variability of the delays.

Finally, since we handled the variability in probabilities for laboratory testing by varying the probability that a specimen is sent to each laboratory, we also held constant at 100% the probability that samples received by laboratories are tested.

We need to find ways to store energy and design electrical grids that can handle the large variability of both electricity demand and supply.

A min max strategy is used to handle the loading variability such that the resulting optimal design is able to withstand an entire class of linear piecewise loadings.

Success in these tasks often requires the integration of various sensor or data modalities such as video, audio, motion, and accompanying text, and typically hinges on a host of machine-learning methodologies to handle the inherent variability and complexity of the ensuing features.

For example, Ardila et al. [41] successfully used an automated region-based active contours approach for multispectral data, which allowed for better addressing realistic crown shapes and could better handle the spectral variability of neighboring pixels, which has been a significant challenge for very high spatial resolution imagery.

More specifically, it requires: (1) to determine which classifier algorithms can handle the amount and the variability of data; (2) to evaluate the stability of classifier parameters; (3) to select the best feature set used as input data in order to find the good trade-off between classification accuracy and computational time; and (4) to establish the classifier accuracy over large areas.

This helps in handling the existing variability or heterogeneity within this semantic.